After genome sequencing, microarray technology has emerged as a widely used platform for genomic studies in the life sciences. DNA microarrays have high-density orderly arrangements of nucleic acid spots. Many research studies have demonstrated the general usefulness of genome probing using microarrays. While simultaneous measurement of thousands of gene expression levels provides a potential source of profound knowledge, success of the microarray technology depends on the precision of the measurements and on the integration of computational tools for data mining, visualization, and statistical modeling. With the abundance of data produced from genomic studies, the greatest challenge is analytical. The impact of genomic and proteomic technology on biology will depend heavily on bioinformatics methods and statistical analysis. Sophisticated data-mining and analytical tools are needed to correlate data obtained from the arrays, to group them in a meaningful way, and to perform statistical analysis in order to investigate hypotheses of interest. Experimental design and statistical methods provide powerful analytical tools to biologist for the study of living systems. Through statistical analysis and the graphical display of clustering and classification results, microarray experiments allow biologists to assimilate and explore the data in a natural and intuitive manner. [unreadable] [unreadable] The conference will cover current research on statistical models and bioinformatics methods for microarray data, proteomic data and population genetics. The conference will provide a forum for discussion on statistical and bioinformatics methods for analyzing genomic data. It will also provide a bridge for smooth transition and statistical methods from the genomic era to the proteomic era. [unreadable] [unreadable] The objective of this conference are to bring together senior and established researchers and young and promising researchers from around the world who are working on the bioinformatics and statistical aspects of genomic data analysis and to share recent and current research work, as well as examine future trends, in these areas. [unreadable] [unreadable] [unreadable]